To test the scalability of AFNO for high resolution images with respect to alternative mixers, we evaluate high-resolution (\(1024 \times 1024\) ) semantic segmentation for the Cityscapes dataset. We use the SegFormer-B3 backbone which is a hiearchical vision transformer [1]}. We train the model using the cross-entropy loss and measure performance via reporting mIoU over the validation set. More details about the experiments and the model are available in the Appendix.
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